Satellite-borne rain radar positioning precision correction method based on sea-land signal distribution difference

Abstract

The invention provides a satellite-borne rain detection radar positioning precision correction method and system based on sea-land signal distribution difference. The method comprises the following steps: determining a longitude and latitude range of an overlapping region; determining a start detection period and a stop detection period by using the screened rain detection radar detection data; calculating a detection signal difference value between the current detection wave position and the previous detection wave position and the detection signal difference value between the current detection wave position and the next detection wave position in the same period to determine a land surface pixel signal threshold value, and extracting land surface distribution pixels; determining the sea-land distribution boundary position of the detection signal and counting the total number of land surface distribution pixels; pixel offset is carried out in the along-rail direction and the cross-rail direction, and the pixel matching coverage rate is calculated; and respectively obtaining the pixel offset numbers in the along-rail direction and the cross-rail direction with the pixel matching coverage rate closest to 1, and completing the positioning precision correction. The method can be used in the research field of satellite-borne rain radar detection signal accurate positioning, and is an effective and important technical means for realizing rain radar detection signal positioning accuracy correction.

Description

Technical Field

[0001] The present invention belongs to the field of precise positioning of satellite-borne rain-measuring radar detection signals, and in particular, relates to a satellite-borne rain-measuring radar positioning accuracy correction method based on differences in sea and land signal distribution. Background Art

[0002] Precipitation processes are often accompanied by disastrous weather systems such as typhoons, heavy rains or severe convection, and are very important weather events. Deepening the understanding of the three-dimensional structural characteristics of precipitation and the characteristics of climate distribution is a prerequisite for achieving meteorological disaster prevention and mitigation. Satellite-borne precipitation radars have huge advantages that cannot be matched by ground-based meteorological observation stations and other observation methods. They can obtain precipitation information in various surface areas such as complex terrain areas, uninhabited areas, and ocean surfaces, and achieve effective detection of instantaneous precipitation on a global scale. The rich precipitation data accumulated by satellite remote sensing detection provide great convenience and data support for conducting research on regional precipitation structure characteristics.

[0003] The preprocessing accuracy of the original detection signal of the satellite-borne precipitation radar is the basis for subsequent data analysis and application. The precipitation radar is affected by transportation, satellite launch, and on-orbit working environment. The load characteristic parameters such as the original line of sight of the radar detection beam will change to a certain extent, resulting in the deviation of the positioning accuracy of the original detection signal, which requires correction of the positioning accuracy.

[0004] At present, for the positioning accuracy correction of satellite remote sensing detection slices, the relevant technology generally compares the positional relationship between the original detection signal distribution and the known ground observation target signal distribution, and uses the target point position matching characteristics of the two types of data to adjust the positioning accuracy. However, this method requires the simultaneous acquisition of the fixed ground observation target position observed by the same remote sensing satellite, which requires manual selection and identification, and there are subjective judgment errors and detection signal distribution position matching errors. At the same time, there are related technologies that adjust the positioning accuracy by modifying the payload parameters on orbit, but the characteristic parameters of the payload to be injected are not easy to obtain, and the correction processing link is long. For example, patent document CN108242047A discloses a CCD-based optical satellite remote sensing image data correction method, which completes image splicing, band registration, geometric distortion correction, and generates high-precision RPC functions by establishing a virtual CCD and a real CCD respectively. The forward and reverse calculation model from the image to the ground longitude and latitude is established.

[0005] Satellite-borne precipitation radar is a microwave active precipitation measurement radar. The detection signal shows obvious differences on the ocean and land surfaces. The relative position difference between the sea-land distribution boundary of the detection signal and the high-precision coastline can be used to correct the positioning accuracy. This method can use a single-track detection signal to complete the positioning accuracy correction, reduce the amount of data required for target position matching, and reduce the errors of manual identification and evaluation of position matching in traditional methods. Therefore, it is necessary to propose a satellite-borne precipitation radar positioning accuracy correction method and system based on the difference in sea and land signal distribution, improve the preprocessing accuracy of satellite-borne precipitation radar detection signals, and better serve the analysis and application of back-end satellite remote sensing data. Summary of the invention

[0006] In view of the defects in the prior art, the object of the present invention is to provide a method for correcting the positioning accuracy of a satellite-borne rainfall radar based on the difference in sea and land signal distribution.

[0007] A method for correcting positioning accuracy of a satellite-borne rainfall radar based on the difference in signal distribution between land and sea provided by the present invention comprises:

[0008] Step S1: Determine the overlapping area according to the relative position of the coastline and the current rainfall radar detection area;

[0009] Step S2: using the overlapping area to filter the rainfall radar detection data;

[0010] Step S3: using the rain measuring radar detection data to determine the start detection period and the end detection period;

[0011] Step S4: for the rain measuring radar detection data between the start detection period and the end detection period, calculating the detection signal difference between the current detection wave position and the previous detection wave position and the next detection wave position in the same detection period;

[0012] Step S5: determining the land surface pixel signal threshold according to the detection signal difference, and extracting the land surface distribution pixels;

[0013] Step S6: determining the sea-land distribution boundary position of the detection signal according to the extracted land distribution pixels and counting the total number of land distribution pixels;

[0014] Step S7: Pixel offset is performed in the along-track and across-track directions, and the pixel matching coverage is calculated based on the total number of pixels distributed on the land surface;

[0015] Step S8: according to the distribution of pixel matching coverage curves in the along-track and across-track directions, respectively obtain the number of pixel offsets in the along-track and across-track directions with pixel matching coverage closest to 1;

[0016] Step S9: Correct the positioning accuracy according to the number of pixel offsets along the track and across the track.

[0017] Preferably, the detection signal differences between the current detection wave position and the previous detection wave position and the next detection wave position are recorded as DF1 and DF2 respectively;

[0018] In step S5, if the DF1 of the pixel in the area near the land-sea boundary is a positive value and the value exceeds the first set value, and the pixel DF2 is a negative value or a positive value that does not exceed the second set value, then it is considered that the detection pixel distribution extends from the ocean surface to the land surface; otherwise, it is considered that the detection pixel extends from the land surface to the ocean surface; the signal values ​​of the pixels that meet the DF1 and DF2 distribution characteristics in all periods are counted, and the minimum value is set as the extraction threshold to obtain the land surface distribution pixels.

[0019] Preferably, in step S6, whether the detection pixel is a land pixel is determined periodically, and combined with the detection pixel position distribution order, whether it extends from the ocean surface to the land surface or from the land surface to the ocean surface, the position of the rain measuring radar detection signal at the sea-land distribution boundary is determined periodically, and the number of land pixels is counted to obtain the total number of land distribution pixels.

[0020] Preferably, in step S7, the pixel matching coverage is calculated using the following formula:

[0021]

[0022] Cov_rate represents the pixel matching coverage;

[0023] Num i It represents the total number of land surface distribution pixels within the coastline during the i-th correction process;

[0024] Num total Represents the total number of land surface distribution pixels in the overlap area.

[0025] According to the present invention, a satellite-borne rainfall radar positioning accuracy correction system based on the difference in sea and land signal distribution is provided, comprising:

[0026] Module M1: Determine the overlapping area based on the relative position of the coastline and the current rainfall radar detection area;

[0027] Module M2: using the overlapping area to filter the rainfall radar detection data;

[0028] Module M3: using the rain radar detection data to determine the start detection period and the end detection period;

[0029] Module M4: for the rain measuring radar detection data between the start detection period and the end detection period, calculate the detection signal difference between the current detection wave position and the previous detection wave position and the next detection wave position in the same detection period;

[0030] Module M5: Determine the land surface pixel signal threshold according to the detection signal difference, and extract the land surface distribution pixels;

[0031] Module M6: determining the sea-land distribution boundary position of the detection signal according to the extracted land distribution pixels and counting the total number of land distribution pixels;

[0032] Module M7: Pixel offset is performed in the along-track and across-track directions, and the pixel matching coverage is calculated based on the total number of pixels distributed on the land surface;

[0033] Module M8: According to the distribution of pixel matching coverage curves in the along-track and across-track directions, the number of pixel offsets in the along-track and across-track directions with pixel matching coverage closest to 1 is obtained respectively;

[0034] Module M9: Complete positioning accuracy correction according to the number of pixel offsets along the track and across the track.

[0035] Preferably, the detection signal differences between the current detection wave position and the previous detection wave position and the next detection wave position are recorded as DF1 and DF2 respectively;

[0036] In the module M5, if the DF1 of the pixel in the area near the land-sea boundary is positive and exceeds the first set value, and the pixel DF2 is negative or positive and does not exceed the second set value, then it is considered that the detection pixel distribution extends from the ocean surface to the land surface; otherwise, it is considered that the detection pixel extends from the land surface to the ocean surface; the signal values ​​of the pixels that meet the DF1 and DF2 distribution characteristics in all periods are counted, and the minimum value is set as the extraction threshold to obtain the land surface distribution pixels.

[0037] Preferably, in the module M6, whether the detection pixel is a land pixel is determined periodically, and combined with the detection pixel position distribution order, whether it extends from the ocean surface to the land surface or from the land surface to the ocean surface, the position of the rain measuring radar detection signal at the sea-land distribution boundary is determined periodically, and the number of land pixels is counted to obtain the total number of land distribution pixels.

[0038] Preferably, in the module M7, the pixel matching coverage is calculated using the following formula:

[0039]

[0040] Cov_rate represents the pixel matching coverage;

[0041] Num i It represents the total number of land surface distribution pixels within the coastline during the i-th correction process;

[0042] Num total Represents the total number of land surface distribution pixels in the overlap area.

[0043] According to a computer-readable storage medium storing a computer program provided by the present invention, when the computer program is executed by a processor, the steps of the method for correcting the positioning accuracy of a satellite-borne rainfall radar based on the difference in sea and land signal distribution are implemented.

[0044] An electronic device provided according to the present invention includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, the steps of the method for correcting the positioning accuracy of a satellite-borne rainfall radar based on the difference in sea and land signal distribution are implemented.

[0045] Compared with the prior art, the present invention has the following beneficial effects:

[0046] 1. The present invention does not need to compare the position of the current detection slice with the fixed ground observation target detection slice or to modify the payload characteristic parameters on-orbit for correction. It does not require a large amount of data matching accuracy evaluation, overcomes the technical problems that manual statistics and judgment will increase the matching error, the injection parameters are not easy to obtain and the processing correction link is long, and fills the gap in the prior art.

[0047] 2. The present invention can be used in the research field of precise positioning of satellite-borne rain-measuring radar detection signals, and is an effective and important technical means to achieve positioning accuracy correction of rain-measuring radar detection signals.

[0048] 3. The present invention compares the obvious differences between the rain radar detection signals on the ocean and land surfaces, and uses the relative position difference between the sea-land distribution boundary of the detection signal and the high-precision coastline to perform positioning accuracy correction. This method can use single-track detection signals to complete positioning accuracy correction, reduce the amount of large data required for target position matching in traditional methods, and reduce the errors of manual statistical identification and evaluation position matching. To a certain extent, it shortens the positioning accuracy correction link of the on-orbit injection load parameters, and improves the preprocessing timeliness and accuracy of the original signal detected by the rain radar. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings:

[0050] Figure 1 It is a schematic diagram of the working method of the present invention.

[0051] Figure 2 This is the original signal distribution diagram of the rain measuring radar in the overlapping area of ​​the present invention.

[0052] Figure 3 This is a distribution map of the coastline of Hainan Province, China in the overlapping area in the present invention.

[0053] Figure 4This is the original detection signal of the rainfall radar in Hainan Province, China and the matching distribution map of the coastline.

[0054] Figure 5 This is a gradient distribution diagram of the same-period signal changes of the rainfall radar in Hainan Province, China in the overlapping area of ​​the present invention.

[0055] Figure 6 This is a schematic diagram of the pixel extraction of land surface distribution in Hainan Province, China in the present invention.

[0056] Figure 7 This is the land-sea boundary distribution map of the rainfall radar detection signal in Hainan Province, China in the present invention.

[0057] Figure 8 This is a distribution map of land surface distribution pixels of rainfall radar detection signals in Hainan Province, China within the coastline range in the present invention.

[0058] Fig. 9 It is the distribution curve of the number of pixel offsets along the track and across the track and the matching pixel coverage rate in the present invention.

[0059] Fig.10 This is a distribution map of the rain radar detection signal and coastline matching after positioning accuracy correction in Hainan Province, China in the present invention. DETAILED DESCRIPTION

[0060] The present invention is described in detail below in conjunction with specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but are not intended to limit the present invention in any form. It should be noted that, for those of ordinary skill in the art, several changes and improvements can also be made without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0061] The invention determines the latitude and longitude range of the overlapping area according to the relative position of the high-precision coastline and the current rain measuring radar detection area; uses the overlapping area range to screen the rain measuring radar detection data and the coastline data; uses the screened rain measuring radar detection data to determine the start and end detection period; calculates the detection signal difference between the current detection wave position and the previous detection wave position and the next detection wave position in the same period; determines the land surface pixel signal threshold according to the detection signal difference, and extracts the land surface distribution pixel; determines the sea and land distribution boundary position of the detection signal and counts the total number of land surface distribution pixels; performs pixel offset in the along-track and cross-track directions, counts the number of land surface distribution pixels, and calculates the pixel matching coverage rate; obtains the number of pixel offsets in the along-track and cross-track directions whose pixel matching coverage rates are closest to 1 according to the distribution of pixel matching coverage rate curves in the along-track and cross-track directions; and completes the positioning accuracy correction according to the number of pixel offsets in the along-track and cross-track directions.

[0062] According to a method for correcting the positioning accuracy of a satellite-borne rainfall radar based on the difference in signal distribution between land and sea, the present invention provides: Figure 1 As shown, the following steps are included:

[0063] Step S1: Determine the latitude and longitude range of the overlapping area according to the relative position of the high-precision coastline and the current rainfall radar detection area. The data detected by the rainfall radar is single-track data, that is, within the single-track range detected by the rainfall radar, select the area that overlaps with the coastline and give the latitude and longitude range of the overlapping area (minimum longitude, maximum longitude, minimum latitude and maximum latitude).

[0064] Step S2: Filter the rainfall radar detection data and coastline data using the overlapping area range. The rainfall radar detection data selects the background noise power data, and filters the single track bottom detection data and coastline data located in the overlapping area according to the latitude and longitude range of the overlapping area.

[0065] Step S3: Determine the start and end detection cycles using the filtered radar detection data. Using the filtered radar detection data, compare the position of each detection pixel with the latitude and longitude range of the overlapping area in each cycle to obtain the cycle (cycle number) of the rain radar detection entering and leaving the overlapping area, which is defined as the start and end detection cycle.

[0066] Step S4: Calculate the detection signal difference between the current detection wave position and the previous detection wave position and the next detection wave position in the same cycle. Using the rain radar detection data between the start and end periods, for each detection wave position in the same cycle, calculate the detection signal difference between the current detection wave position and the previous detection wave position and the next detection wave position, which are recorded as DF1 and DF2 respectively.

[0067] Step S5: Determine the land pixel signal threshold according to the detection signal difference, and extract the land distribution pixels. Using the detection signal difference DF1 and DF2, if the DF1 of the pixel in the area near the sea-land boundary is positive and the value is large, and the pixel DF2 is negative or a small positive value, then it means that the detection pixel distribution extends from the ocean surface to the land surface, and vice versa. Therefore, if the detection pixel position is distributed from the ocean surface to the land surface, the detection signal value in each cycle shows an increasing trend, and the signal values ​​of the pixels that meet the DF1 and DF2 distribution characteristics in all cycles are counted, and the minimum value is set as the extraction threshold. For the rain radar detection signal in the overlapping area, the land distribution pixels are extracted using the extraction threshold.

[0068] Step S6: Determine the position of the sea-land distribution boundary of the detection signal and count the total number of land distribution pixels. Using the land pixels in the overlapping area, determine whether the detection pixel is a land pixel periodically, and combine the detection pixel position distribution sequence (extending from the ocean surface to the land surface or from the land surface to the ocean surface) to determine the position of the rain measuring radar detection signal at the sea-land distribution boundary periodically, and count the number of land pixels to obtain the total number of land distribution pixels.

[0069] Step S7: Pixel shifting is performed in the along-track and cross-track directions, the number of pixels distributed on the land surface is counted, and the pixel matching coverage rate is calculated. The positioning accuracy correction process is decomposed into the positioning accuracy correction process of the satellite along-track detection and cross-track detection directions, that is, pixel shifting is performed in the along-track and cross-track directions. In each shifting process, the total number of pixels distributed on the land surface within the coastline is calculated, and the total number of pixels distributed on the land surface in the overlapping area is combined with the calculated pixel matching coverage rate. The calculation formula is as follows:

[0070]

[0071] Among them, Cov_rate represents the pixel matching coverage rate, Num i Indicates the total number of land surface distribution pixels within the coastline during the i-th correction process, Num total Represents the total number of land surface distribution pixels in the overlap area.

[0072] Step S8: According to the pixel matching coverage rate curve distribution along the track and across the track, the number of pixel offsets along the track and across the track with the pixel matching coverage rate closest to 1 is obtained respectively. The pixel matching coverage rate curve along the track and across the track is formed by using the corresponding pixel matching coverage rate during the multiple pixel offset processes. In each curve distribution, the number of offset pixels corresponding to the pixel matching coverage rate closest to 1 can be found, that is, the offset amount of the total number of land surface distribution pixels within the coastline range closest to the total number of land surface distribution pixels in the overlapping area. Then the optimal number of pixel offsets along the track and across the track is obtained.

[0073] Step S9: Correct the positioning accuracy according to the number of pixel offsets in the along-track and cross-track directions. Correct the original positioning accuracy by using the number of pixel offsets in the along-track and cross-track directions to improve the accuracy of the preprocessing of the rain radar detection data.

[0074] Furthermore, combined with Figures 1 to 10 The satellite-borne rainfall radar positioning accuracy correction method based on the difference in sea and land signal distribution of the present invention is specifically described as follows:

[0075] The latitude and longitude range of the overlapping area is determined based on the relative position of the high-precision coastline and the current rainfall radar detection area. The rainfall radar detection data is single-track data, that is, within the single-track range detected by the rainfall radar, the area that overlaps with the coastline is selected to give the latitude and longitude range of the overlapping area (minimum longitude, maximum longitude, minimum latitude and maximum latitude).

[0076] The overlapping area is used to filter the rain radar detection data and coastline data. The rain radar detection data selects the background noise power data, and according to the latitude and longitude range of the overlapping area, the single track detection data and coastline data in the overlapping area are filtered. The original signal distribution of the rain radar in the overlapping area is as follows: Figure 2 The distribution of coastlines in the overlapping area is shown in Figure 3 shown.

[0077] The start and end detection cycles are determined by using the filtered radar detection data. The filtered radar detection data is used to compare the position of each detection pixel with the latitude and longitude range of the overlapping area in each cycle to obtain the cycle (cycle number) of the rain radar detection entering and leaving the overlapping area, which is defined as the start and end detection cycle. The original detection signal of the rain radar and the matching distribution of the coastline are shown in the figure. Figure 4 shown.

[0078] Calculate the detection signal difference between the current detection wave position and the previous detection wave position and the next detection wave position in the same cycle. Using the detection data of the rain radar between the start and end cycles, in the same cycle, for each detection wave position, calculate the detection signal difference between the current detection wave position and the previous detection wave position and the next detection wave position, which are recorded as DF1 and DF2 respectively. The gradient distribution of the same-period signal change of the rain radar in the overlapping area is as follows: Figure 5 shown.

[0079] Determine the land surface pixel signal threshold based on the detection signal difference, and extract the land surface distribution pixels. Using the detection signal differences DF1 and DF2, if the DF1 of the pixel in the area near the sea-land boundary is positive and large, and the pixel DF2 is negative or a small positive value, then it means that the detection pixel distribution extends from the ocean surface to the land surface, and vice versa. Therefore, if the detection pixel position is distributed from the ocean surface to the land surface, the detection signal value in each cycle shows an increasing trend, and the signal values ​​of the pixels that meet the DF1 and DF2 distribution characteristics in all cycles are counted, and the minimum value is set as the extraction threshold. For the rain radar detection signal in the overlapping area, the land surface distribution pixels are extracted using the extraction threshold. The schematic diagram of land surface distribution pixel extraction is shown in the figure. Figure 6 shown.

[0080] Determine the position of the sea-land distribution boundary of the detection signal and count the total number of land distribution pixels. Using the land distribution pixels in the overlapping area, determine whether the detection pixel is a land pixel periodically, and combine the distribution sequence of the detection pixel positions (extending from the ocean to the land or from the land to the ocean) to determine the position of the sea-land distribution boundary of the rain radar detection signal periodically. The sea-land boundary distribution of the rain radar detection signal is as follows: Figure 7 The number of land surface pixels is counted period by period to obtain the total number of land surface distribution pixels. The land surface distribution pixels of the rainfall radar detection signal are distributed within the coastline as shown in the figure below. Figure 8 shown.

[0081] Pixel offsets are performed along the track and across the track, the number of pixels distributed on the land surface is counted, and the pixel matching coverage rate is calculated. The positioning accuracy correction process is decomposed into the positioning accuracy correction process of the satellite along the track detection and across the track detection direction, that is, pixel offsets are performed along the track and across the track. In each offset process, the total number of pixels distributed on the land surface within the coastline is calculated. Combined with the total number of pixels distributed on the land surface in the overlapping area and the calculated pixel matching coverage rate, the calculation formula is as follows:

[0082]

[0083] Among them, Cov_rate represents the pixel matching coverage rate, Num i Indicates the total number of land surface distribution pixels within the coastline during the i-th correction process, Num total Represents the total number of land surface distribution pixels in the overlap area.

[0084] According to the pixel matching coverage rate curve distribution along the track and across the track, the number of pixel offsets in the along-track and across-track directions with the pixel matching coverage rate closest to 1 is obtained respectively. The pixel matching coverage rate corresponding to the multiple pixel offset processes is used to form the pixel matching coverage rate curve along the track and across the track. In each curve distribution, the number of offset pixels corresponding to the pixel matching coverage rate closest to 1 can be found, that is, the offset amount of the total number of pixels distributed on the land surface within the coastline range closest to the total number of pixels distributed on the land surface in the overlapping area. Then the optimal number of pixel offsets in the along-track and across-track directions is obtained. The distribution curve between the number of pixel offsets in the along-track and across-track directions and the matching pixel coverage rate is shown as follows: Fig. 9 shown.

[0085] The positioning accuracy is corrected according to the number of pixel offsets in the along-track and across-track directions. The original positioning accuracy is corrected by using the number of pixel offsets in the along-track and across-track directions to improve the accuracy of the preprocessing of the rain radar detection data. The matching distribution of the rain radar detection signal after positioning accuracy correction and the coastline is shown in the figure below: Fig.10 It can be seen that after the positioning accuracy correction of the rainfall radar detection signal, the matching accuracy of the sea and land distribution boundary of the detection signal and the high-precision coastline is significantly improved.

[0086] The present invention also provides a satellite-borne rain measuring radar positioning accuracy correction system based on the difference in signal distribution between sea and land. The satellite-borne rain measuring radar positioning accuracy correction system based on the difference in signal distribution between sea and land can be realized by executing the process steps of the satellite-borne rain measuring radar positioning accuracy correction method based on the difference in signal distribution between sea and land, that is, those skilled in the art can understand the satellite-borne rain measuring radar positioning accuracy correction method based on the difference in signal distribution between sea and land as a preferred implementation of the satellite-borne rain measuring radar positioning accuracy correction system based on the difference in signal distribution between sea and land.

[0087] According to the present invention, a satellite-borne rainfall radar positioning accuracy correction system based on the difference in sea and land signal distribution is provided, comprising:

[0088] Module M1: Determine the latitude and longitude range of the overlapping area according to the relative position of the high-precision coastline and the current rainfall radar detection area. The rainfall radar detection data is single-track data, that is, within the single-track range detected by the rainfall radar, select the area that overlaps with the coastline and give the latitude and longitude range of the overlapping area (minimum longitude, maximum longitude, minimum latitude and maximum latitude).

[0089] Module M2: Filtering the rainfall radar detection data and coastline data using the overlapping area range. The rainfall radar detection data selects the background noise power data, and filters the single-track bottom detection data and coastline data located in the overlapping area according to the latitude and longitude range of the overlapping area.

[0090] Module M3: Determine the start and end detection cycle using the filtered radar detection data. Using the filtered radar detection data, compare the position of each detection pixel with the latitude and longitude range of the overlapping area in each cycle to obtain the cycle (cycle number) of the rain radar detection entering and leaving the overlapping area, which is defined as the start and end detection cycle.

[0091] Module M4: Calculate the detection signal difference between the current detection wave position and the previous detection wave position and the next detection wave position in the same cycle. Using the rain radar detection data between the start and end periods, for each detection wave position in the same cycle, calculate the detection signal difference between the current detection wave position and the previous detection wave position and the next detection wave position, which are recorded as DF1 and DF2 respectively.

[0092] Module M5: Determine the land pixel signal threshold according to the detection signal difference, and extract the land distribution pixels. Using the detection signal difference DF1 and DF2, if the DF1 of the pixel in the area near the sea-land boundary is positive and the value is large, and the pixel DF2 is negative or a small positive value, then it means that the detection pixel distribution extends from the ocean surface to the land surface, and vice versa. Therefore, if the detection pixel position is distributed from the ocean surface to the land surface, the detection signal value in each cycle shows an increasing trend, and the signal values ​​of the pixels that meet the DF1 and DF2 distribution characteristics in all cycles are counted, and the minimum value is set as the extraction threshold. For the rain radar detection signal in the overlapping area, the land distribution pixels are extracted using the extraction threshold.

[0093] Module M6: Determine the position of the sea-land distribution boundary of the detection signal and count the total number of land distribution pixels. Using the land pixels in the overlapping area, determine whether the detection pixel is a land pixel periodically, and combine the distribution order of the detection pixel position (extending from the ocean surface to the land surface or from the land surface to the ocean surface), determine the position of the rain detection radar detection signal at the sea-land distribution boundary periodically, and count the number of land pixels to obtain the total number of land distribution pixels.

[0094] Module M7: Pixel offset is performed in the along-track and cross-track directions, the number of pixels distributed on the land surface is counted, and the pixel matching coverage rate is calculated. The positioning accuracy correction process is decomposed into the positioning accuracy correction process of the satellite along-track detection and cross-track detection directions, that is, pixel offset is performed in the along-track and cross-track directions. In each offset process, the total number of pixels distributed on the land surface within the coastline is calculated. Combined with the total number of pixels distributed on the land surface in the overlapping area and the calculated pixel matching coverage rate, the calculation formula is as follows:

[0095]

[0096] Among them, Cov_rate represents the pixel matching coverage rate, Num i Indicates the total number of land surface distribution pixels within the coastline during the i-th correction process, Num total Represents the total number of land surface distribution pixels in the overlap area.

[0097] Module M8: According to the pixel matching coverage rate curve distribution along the track and across the track, the number of pixel offsets along the track and across the track with the pixel matching coverage rate closest to 1 is obtained respectively. The pixel matching coverage rate curves along the track and across the track are formed using the corresponding pixel matching coverage rates during the multiple pixel offset processes. The number of offset pixels corresponding to the pixel matching coverage rate closest to 1 can be found in each curve distribution, that is, the offset amount of the total number of land surface distribution pixels within the coastline range closest to the total number of land surface distribution pixels in the overlapping area. Then the optimal number of pixel offsets along the track and across the track is obtained.

[0098] Module M9: Correct the positioning accuracy according to the number of pixel offsets along the track and across the track. The original positioning accuracy is corrected by using the number of pixel offsets along the track and across the track to improve the accuracy of the preprocessing of the rain radar detection data.

[0099] According to a computer-readable storage medium storing a computer program provided by the present invention, when the computer program is executed by a processor, the steps of the method for correcting the positioning accuracy of a satellite-borne rainfall radar based on the difference in sea and land signal distribution are implemented.

[0100] Those skilled in the art know that, in addition to realizing the system and its various devices, modules, and units provided by the present invention in a purely computer-readable program code, it is entirely possible to realize the same functions in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers by logically programming the method steps. Therefore, the system and its various devices, modules, and units provided by the present invention can be considered as a hardware component, and the devices, modules, and units included therein for realizing various functions can also be regarded as structures within the hardware component; the devices, modules, and units for realizing various functions can also be regarded as both software modules for realizing the method and structures within the hardware component.

[0101] The above describes the specific embodiments of the present invention. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art can make various changes or modifications within the scope of the claims, which does not affect the essence of the present invention. In the absence of conflict, the embodiments of the present application and the features in the embodiments can be combined with each other arbitrarily.

Claims

1. A method for correcting the positioning accuracy of a satellite-borne rainfall radar based on the difference in signal distribution between land and sea, characterized in that: include: Step S1: Determine the overlapping area according to the relative position of the coastline and the current rainfall radar detection area; Step S2: using the overlapping area to filter the rainfall radar detection data; Step S3: using the rain measuring radar detection data to determine the start detection period and the end detection period; Step S4: for the rain measuring radar detection data between the start detection period and the end detection period, calculating the detection signal difference between the current detection wave position and the previous detection wave position and the next detection wave position in the same detection period; Step S5: determining the land surface pixel signal threshold according to the detection signal difference, and extracting the land surface distribution pixels; Step S6: determining the sea-land distribution boundary position of the detection signal according to the extracted land distribution pixels and counting the total number of land distribution pixels; Step S7: Pixel offset is performed in the along-track and across-track directions, and the pixel matching coverage is calculated based on the total number of pixels distributed on the land surface; Step S8: according to the distribution of pixel matching coverage curves in the along-track and across-track directions, respectively obtain the number of pixel offsets in the along-track and across-track directions with pixel matching coverage closest to 1; Step S9: Correct the positioning accuracy according to the number of pixel offsets along the track and across the track.

2. The method for correcting the positioning accuracy of satellite-borne rainfall radar based on the difference in sea and land signal distribution according to claim 1 is characterized in that: The detection signal differences between the current detection wave position and the previous detection wave position and the next detection wave position are recorded as DF1 and DF2 respectively; In step S5, if the DF1 of the pixel in the area near the land-sea boundary is positive and exceeds the first set value, and the pixel DF2 is negative or positive and does not exceed the second set value, then it is considered that the detection pixel distribution extends from the ocean surface to the land surface; otherwise, it is considered that the detection pixel extends from the land surface to the ocean surface; the signal values ​​of the pixels that meet the DF1 and DF2 distribution characteristics in all periods are counted, and the minimum value is set as the extraction threshold to obtain the land surface distribution pixels.

3. The method for correcting the positioning accuracy of satellite-borne rainfall radar based on the difference in signal distribution between land and sea according to claim 1, characterized in that: In step S6, whether the detection pixel is a land pixel is determined periodically, and combined with the detection pixel position distribution order, whether it extends from the ocean surface to the land surface or from the land surface to the ocean surface, the position of the rain measuring radar detection signal at the sea-land distribution boundary is determined periodically, and the number of land pixels is counted to obtain the total number of land distribution pixels.

4. The method for correcting the positioning accuracy of satellite-borne rainfall radar based on the difference in sea and land signal distribution according to claim 1 is characterized in that: In step S7, the pixel matching coverage is calculated, and the calculation formula is as follows: Cov_rate represents the pixel matching coverage; Num i It represents the total number of land surface distribution pixels within the coastline during the i-th correction process; Num total Represents the total number of land surface distribution pixels in the overlap area.

5. A satellite-borne rainfall radar positioning accuracy correction system based on the difference in sea and land signal distribution, characterized in that: include: Module M1: Determine the overlapping area based on the relative position of the coastline and the current rainfall radar detection area; Module M2: using the overlapping area to filter the rainfall radar detection data; Module M3: using the rain radar detection data to determine the start detection period and the end detection period; Module M4: for the rain measuring radar detection data between the start detection period and the end detection period, calculate the detection signal difference between the current detection wave position and the previous detection wave position and the next detection wave position in the same detection period; Module M5: Determine the land surface pixel signal threshold according to the detection signal difference, and extract the land surface distribution pixels; Module M6: determining the sea-land distribution boundary position of the detection signal according to the extracted land distribution pixels and counting the total number of land distribution pixels; Module M7: Pixel offset is performed in the along-track and across-track directions, and the pixel matching coverage is calculated based on the total number of pixels distributed on the land surface; Module M8: According to the distribution of pixel matching coverage curves in the along-track and across-track directions, the number of pixel offsets in the along-track and across-track directions with pixel matching coverage closest to 1 is obtained respectively; Module M9: Correction of positioning accuracy is performed based on the number of pixel offsets along the track and across the track.

6. The satellite-borne rainfall radar positioning accuracy correction system based on the difference in sea and land signal distribution according to claim 5 is characterized in that: The detection signal differences between the current detection wave position and the previous detection wave position and the next detection wave position are recorded as DF1 and DF2 respectively; In the module M5, if the DF1 of the pixel in the area near the land-sea boundary is positive and exceeds the first set value, and the pixel DF2 is negative or positive and does not exceed the second set value, then it is considered that the detection pixel distribution extends from the ocean surface to the land surface; otherwise, it is considered that the detection pixel extends from the land surface to the ocean surface; the signal values ​​of the pixels that meet the DF1 and DF2 distribution characteristics in all periods are counted, and the minimum value is set as the extraction threshold to obtain the land surface distribution pixels.

7. The satellite-borne rainfall radar positioning accuracy correction system based on the difference in sea and land signal distribution according to claim 5 is characterized in that: In the module M6, whether the detection pixel is a land pixel is determined periodically, and combined with the position distribution order of the detection pixels, whether it extends from the ocean surface to the land surface or from the land surface to the ocean surface, the position of the rain measuring radar detection signal at the sea-land distribution boundary is determined periodically, and the number of land pixels is counted to obtain the total number of land distribution pixels.

8. The satellite-borne rainfall radar positioning accuracy correction system based on the difference in sea and land signal distribution according to claim 5 is characterized in that: In the module M7, the pixel matching coverage is calculated, and the calculation formula is as follows: Cov_rate represents the pixel matching coverage; Num i It represents the total number of land surface distribution pixels within the coastline during the i-th correction process; Num total Represents the total number of land surface distribution pixels in the overlap area.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method for correcting the positioning accuracy of a satellite-borne rainfall radar based on the difference in sea and land signal distribution as described in any one of claims 1 to 4 are implemented.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the computer program is executed by a processor, the steps of the method for correcting the positioning accuracy of a satellite-borne rainfall radar based on the difference in sea and land signal distribution as described in any one of claims 1 to 4 are implemented.

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